Assessing impact of poor accrual on premature trial closure requires a relevant metric. We propose defining accrual sufficiency on apparent ability to address primary endpoints (PE) rather than attaining accrual targets.
All phase III trials open January 1, 1993, to December 31, 2002, by five U.S. oncology Clinical Trials Cooperative Groups (CTCG) were evaluated for accrual sufficiency and scientific results. Sufficient accrual included meeting accrual target, CTCGs documentation attesting adequate accrual, or conclusive results at interim analysis; insufficient accrual included poor accrual as cited closure reason or other reasons rendering a trial unable to address its primary endpoints. Closure rates based on our accrual sufficiency definition are compared with rates of meeting accrual targets and addressing the primary endpoints. A percentage of target accrual above which trials commonly answer the intended scientific question was identified to serve as an alternative to meeting full target accrual in designating accrual success.
Of 238 eligible trials, 158 (66%) closed with sufficient accrual. Among 80 trials with insufficient accrual, 70 (29%) closed specifically because of poor accrual. Inadequate accrual rates are overemphasized when defining accrual success solely by meeting accrual targets. Nearly 75% of trials conclusively addressed the primary endpoints with positive results in 39% of trials. Exceeding 80% of target accrual serves as a reliable proxy for answering the intended scientific question.
Approximately one third of phase III trials closed with insufficient accrual to address the primary endpoints, primarily due to poor accrual. Defining accrual sufficiency broader than meeting accrual targets represents a fairer account of trial closures.
A major challenge for randomized phase III oncology trials is the frequent low rates of patient enrollment, resulting in high rates of premature closure due to insufficient accrual.
We conducted a pilot study to determine the extent of trial closure due to poor accrual, feasibility of identifying trial factors associated with sufficient accrual, impact of redesign strategies on trial accrual, and accrual benchmarks designating high failure risk in the clinical trials cooperative group (CTCG) setting.
A subset of phase III trials opened by five CTCGs between August 1991 and March 2004 was evaluated. Design elements, experimental agents, redesign strategies, and pretrial accrual assessment supporting accrual predictions were abstracted from CTCG documents. Percent actual/predicted accrual rate averaged per month was calculated. Trials were categorized as having sufficient or insufficient accrual based on reason for trial termination. Analyses included univariate and bivariate summaries to identify potential trial factors associated with accrual sufficiency.
Among 40 trials from one CTCG, 21 (52.5%) trials closed due to insufficient accrual. In 82 trials from five CTCGs, therapeutic trials accrued sufficiently more often than nontherapeutic trials (59% vs 27%, p = 0.05). Trials including pretrial accrual assessment more often achieved sufficient accrual than those without (67% vs 47%, p = 0.08). Fewer exclusion criteria, shorter consent forms, other CTCG participation, and trial design simplicity were not associated with achieving sufficient accrual. Trials accruing at a rate much lower than predicted (<35% actual/predicted accrual rate) were consistently closed due to insufficient accrual.
This trial subset under-represents certain experimental modalities. Data sources do not allow accounting for all factors potentially related to accrual success.
Trial closure due to insufficient accrual is common. Certain trial design factors appear associated with attaining sufficient accrual. Defining accrual benchmarks for early trial termination or redesign is feasible, but better accrual prediction methods are critically needed. Future studies should focus on identifying trial factors that allow more accurate accrual predictions and strategies that can salvage open trials experiencing slow accrual.
Postoperative outcomes of patients undergoing laparoscopic-assisted colectomy (LAC) have shown modest improvements in recovery but only minimal differences in quality of life (QOL) compared with open colectomy. We therefore sought to assess the effect of LAC on QOL in the short and long term, using individual item analysis of multi-item QOL assessments.
QOL variables were analyzed in 449 randomized patients from the COST trial 93-46-53 (INT 0146). Both cross-sectional single-time and change from baseline assessments were run at day 2, week 2, month 2, and month 18 postoperatively in an intention-to-treat analysis using Wilcoxon rank-sum tests. Stepwise regression models were used to determine predictors of QOL.
Of 449 colon cancer patients, 230 underwent LAC and 219 underwent open colectomy. Subdomain analysis revealed a clinically moderate improvement from baseline for LAC in total QOL index at 18 months (P = 0.02) as well as other small symptomatic improvements. Poor preoperative QOL as indicated by a rating scale of ≤ 50 was an independent predictor of poor QOL at 2 months postoperatively. QOL variables related to survival were baseline support (P = 0.001) and baseline outlook (P = 0.01).
Eighteen months after surgery, any differences in quality of life between patients randomized to LAC or open colectomy favored LAC. However, the magnitude of the benefits was small. Patients with poor preoperative QOL appear to be at higher risk for difficult postoperative courses, and may be candidates for enhanced ancillary services to address their particular needs.
With the advent of targeted therapies, biomarkers provide a promising means of individualizing therapy through an integrated approach to prediction using the genetic makeup of the disease and the genotype of the patient. Biomarker validation has therefore become a central topic of discussion in the field of medicine, primarily due to the changing landscape of therapies for treatment of a disease and these therapies purported mechanism(s) of action.
In this report, we discuss the merits and limitations of some of the clinical trial designs for predictive biomarker validation using examples from ongoing or completed clinical trials.
The designs are broadly classified as retrospective (i.e., using data from previously well-conducted randomized controlled trials (RCT)) versus prospective (enrichment or targeted, unselected or all-comers, hybrid, and adaptive analysis). We discuss some of these designs in the context of real trials.
Well-designed retrospective analysis of prospective RCT can bring forward effective treatments to marker defined subgroup of patients in a timely manner. An example is the KRAS gene status in colorectal cancer – the benefit from cetuximab and panitumumab was demonstrated to be restricted to patients with wild type status based on prospectively specified analyses using data from previously conducted RCTs. Prospective enrichment designs are appropriate when compelling preliminary evidence suggests that not all patients will benefit from the study treatment under consideration; however, this may sometimes leave questions unanswered. An example is the established benefit of trastuzumab as adjuvant therapy for breast cancer; a clear definition of HER2-positivity and the assay reproducibility have, however, remained unanswered. An all-comers design is optimal where preliminary evidence regarding treatment benefit and assay reproducibility is uncertain (e.g., EGFR expression and tyrosine kinase inhibitors in lung cancer), or to identify the most effective therapy from a panel of regimens (e.g., chemotherapy options in breast cancer).
The designs discussed here rest on the assumption that the technical feasibility, assay performance metrics, and the logistics of specimen collection are well established and that initial results demonstrate promise with regard to the predictive ability of the marker(s).
The choice of a clinical trial design is driven by a combination of scientific, clinical, statistical, and ethical considerations. There is no one size fits all solution to predictive biomarker validation.
Prospective trial design often occurs in the presence of “acceptable”  historical control data. Typically this data is only utilized for treatment comparison in a posteriori retrospective analysis to estimate population-averaged effects in a random-effects meta-analysis.
We propose and investigate an adaptive trial design in the context of an actual randomized controlled colorectal cancer trial. This trial, originally reported by Goldberg et al. , succeeded a similar trial reported by Saltz et al. , and used a control therapy identical to that tested (and found beneficial) in the Saltz trial.
The proposed trial implements an adaptive randomization procedure for allocating patients aimed at balancing total information (concurrent and historical) among the study arms. This is accomplished by assigning more patients to receive the novel therapy in the absence of strong evidence for heterogeneity among the concurrent and historical controls. Allocation probabilities adapt as a function of the effective historical sample size (EHSS) characterizing relative informativeness defined in the context of a piecewise exponential model for evaluating time to disease progression. Commensurate priors  are utilized to assess historical and concurrent heterogeneity at interim analyses and to borrow strength from the historical data in the final analysis. The adaptive trial’s frequentist properties are simulated using the actual patient-level historical control data from the Saltz trial and the actual enrollment dates for patients enrolled into the Goldberg trial.
Assessing concurrent and historical heterogeneity at interim analyses and balancing total information with the adaptive randomization procedure leads to trials that on average assign more new patients to the novel treatment when the historical controls are unbiased or slightly biased compared to the concurrent controls. Large magnitudes of bias lead to approximately equal allocation of patients among the treatment arms. Using the proposed commensurate prior model to borrow strength from the historical data, after balancing total information with the adaptive randomization procedure, provides admissible estimators of the novel treatment effect with desirable bias-variance trade-offs.
Adaptive randomization methods in general are sensitive to population drift and more suitable for trials that initiate with gradual enrollment. Balancing information among study arms in time-to-event analyses is difficult in the presence of informative right-censoring.
The proposed design could prove important in trials that follow recent evaluations of a control therapy. Efficient use of the historical controls is especially important in contexts where reliance on pre-existing information is unavoidable because the control therapy is exceptionally hazardous, expensive, or the disease is rare.
adaptive designs; Bayesian analysis; historical controls
Providing personalized treatments designed to maximize benefits and minimizing harms is of tremendous current medical interest. One problem in this area is the evaluation of the interaction between the treatment and other predictor variables. Treatment effects in subgroups having the same direction but different magnitudes are called quantitative interactions, while those having opposite directions in subgroups are called qualitative interactions (QIs). Identifying QIs is challenging since they are rare and usually unknown among many potential biomarkers. Meanwhile, subgroup analysis reduces the power of hypothesis testing and multiple subgroup analyses inflate the type I error rate. We propose a new Bayesian approach to search for QI in a multiple regression setting with adaptive decision rules. We consider various regression models for the outcome. This method is illustrated in two examples of Phase III clinical trials. The algorithm is straightforward and easy to implement using existing software packages. A sample code was provided in the appendix.
Interaction; Subgroup; Predictive Marker; Prognostic Marker; Clinical Trial
PIP aquaporin responses to drought stress can vary considerably depending on the isoform, tissue, species or level of stress; however, a general down-regulation of these genes is thought to help reduce water loss and prevent backflow of water to the drying soil. It has been suggested therefore, that it may be necessary for the plant to limit aquaporin production during drought stress, but it is unknown whether aquaporin down-regulation is gradual or triggered by a particular intensity of the stress. In this study, ten Fragaria PIP genes were identified from the woodland strawberry (Fragaria vesca L.) genome sequence and characterised at the sequence level. The water relations of F. vesca were investigated and the effect of different intensities of drought stress on the expression of four PIP genes, as well as how drought stress influences their diurnal transcription was determined. PIP down-regulation in the root corresponded to the level of drought stress. Moreover, transcript abundance of two genes highly expressed in the root (FvPIP1;1 and FvPIP2;1) was strongly correlated to the decline in substrate moisture content. The amplitude of diurnal aquaporin expression in the leaves was down-regulated by drought without altering the pattern, but showing an intensity-dependent effect. The results show that transcription of PIP aquaporins can be fine-tuned with the environment in response to declining water availability.
Although the importance of obesity in colon cancer risk and outcome is recognized, the association of body mass index (BMI) with DNA mismatch repair (MMR) status is unknown.
Patients and Methods
BMI (kg/m2) was determined in patients with TNM stage II or III colon carcinomas (n = 2,693) who participated in randomized trials of adjuvant chemotherapy. The association of BMI with MMR status and survival was analyzed by logistic regression and Cox models, respectively.
Overall, 427 (16%) tumors showed deficient MMR (dMMR), and 630 patients (23%) were obese (BMI ≥ 30 kg/m2). Obesity was significantly associated with younger age (P = .021), distal tumor site (P = .012), and a lower rate of dMMR tumors (10% v 17%; P < .001) compared with normal weight. Obesity remained associated with lower rates of dMMR (odds ratio, 0.57; 95% CI, 0.41 to 0.79; P < .001) after adjusting for tumor site, stage, sex, and age. Among obese patients, rates of dMMR were lower in men compared with women (8% v 13%; P = .041). Obesity was associated with higher recurrence rates (P = .0034) and independently predicted worse disease-free survival (DFS; hazard ratio [HR], 1.37; 95% CI, 1.14 to 1.64; P = .0010) and overall survival (OS), whereas dMMR predicted better DFS (HR, 0.59; 95% CI, 0.47 to 0.74; P < .001) and OS. The favorable prognosis of dMMR was maintained in obese patients.
Colon cancers from obese patients are less likely to show dMMR, suggesting obesity-related differences in the pathogenesis of colon cancer. Although obesity was independently associated with adverse outcome, the favorable prognostic impact of dMMR was maintained among obese patients.
Purpose of review
To review data demonstrating the prognostic and predictive impact of microsatellite instability (MSI) in human colon carcinomas.
MSI is a molecular marker of defective DNA mismatch repair that is detected in approximately 15% of sporadic colon cancers. Most, but not all retrospective studies, have shown that colon cancers with MSI have better stage-adjusted survival rates compared with non-MSI tumors. Furthermore, analyses of colon cancers from participants in randomized adjuvant therapy trials have suggested that MSI tumors do not benefit from treatment with 5-fluorouracil. Recent studies, including a pooled analysis, validate prior data demonstrating the prognostic and predictive impact of MSI status in colon cancer.
MSI is a molecular marker that can provide valuable prognostic and predictive information in colon cancer patients. In the appropriate clinical setting, MSI data can be used in clinical decision-making. Specifically, the favorable outcome of stage II colon cancers with MSI indicates that such patients should not receive adjuvant chemotherapy. Although data for stage III colon cancers with MSI suggest a lack of benefit from 5-fluorouracil alone, the benefit of the current standard treatment, 5-fluorouracil, leucovorin, and oxaliplatin, in this subgroup remains unknown and awaits further study.
colon cancer; microsatellite instability; prediction; prognosis
Biomarkers are critical to targeted therapies as they may identify patients more likely to benefit from a treatment. Several prospective designs for biomarker directed therapy have been previously proposed, differing primarily in the study population, randomization scheme, or both. Recognizing the need for randomization yet acknowledging the possibility of promising but inconclusive results after a Stage I cohort of randomized patients, we propose a two-stage Phase II design on marker-positive patients that allows for direct assignment in a Stage II cohort. In Stage I, marker-positive patients are equally randomized to receive experimental treatment or control. Stage II has the option to adopt “direct assignment” whereby all patients receive experimental treatment. Through simulation, we studied the power and type I error rate (T1ER) of our design compared to a balanced randomized two-stage design, and performed sensitivity analyses to study the effect of timing of Stage I analysis, population shift effects and unbalanced randomization. Our proposed design has minimal loss in power (<1.8%) and increase in T1ER (<2.1%) compared to a balanced randomized design. The maximum increase in T1ER in the presence of a population shift was between 3.1–5%; the loss in power across possible timings of Stage I analysis was <1.2%. Our proposed design has desirable statistical properties with potential appeal in practice. The direct assignment option, if adopted, provides for an “extended confirmation phase” as an alternative to stopping the trial early for evidence of efficacy in Stage I.
phase II; biomarker; direct assignment
Microsatellite instability (MSI) is the molecular fingerprint of the deficient mismatch repair (MMR) system that characterizes approximately 15% of colorectal cancers (CRCs). MSI develops due to germline mutations in MMR genes or more commonly, from epigenetic silencing of MLH1 in sporadic tumors that occurs in a background of methylation of CpG islands in gene promoter regions and in tumors that frequently show hotspot mutations in the BRAF oncogene. MSI tumors have distinct phenotypic features and have been consistently associated with a better stage-adjusted prognosis compared to microsatellite stable tumors. MSI negatively predicts response to 5-fluorouracil and may also determine responsiveness to other drugs used in CRC treatment. Recent data expand the molecular heterogeneity of MSI tumors that may contribute to the understanding of differential chemosensitivity. Identifying deficient MMR has important implications for patient management and its exploitation holds promise for improving patient outcomes and for the development of novel therapeutics.
Microsatellite instability; deficient DNA mismatch repair; colorectal cancer; prognosis; therapy
The evaluation of surrogate endpoints for primary use in future clinical trials is an increasingly important research area, due to demands for more efficient trials coupled with recent regulatory acceptance of some surrogates as ‘valid.’ However, little consideration has been given to how a trial which utilizes a newly-validated surrogate endpoint as its primary endpoint might be appropriately designed. We propose a novel Bayesian adaptive trial design that allows the new surrogate endpoint to play a dominant role in assessing the effect of an intervention, while remaining realistically cautious about its use. By incorporating multi-trial historical information on the validated relationship between the surrogate and clinical endpoints, then subsequently evaluating accumulating data against this relationship as the new trial progresses, we adaptively guard against an erroneous assessment of treatment based upon a truly invalid surrogate. When the joint outcomes in the new trial seem plausible given similar historical trials, we proceed with the surrogate endpoint as the primary endpoint, and do so adaptively–perhaps stopping the trial for early success or inferiority of the experimental treatment, or for futility. Otherwise, we discard the surrogate and switch adaptive determinations to the original primary endpoint. We use simulation to test the operating characteristics of this new design compared to a standard O’Brien-Fleming approach, as well as the ability of our design to discriminate trustworthy from untrustworthy surrogates in hypothetical future trials. Furthermore, we investigate possible benefits using patient-level data from 18 adjuvant therapy trials in colon cancer, where disease-free survival is considered a newly-validated surrogate endpoint for overall survival.
Bayesian adaptive design; Clinical trials; Surrogate endpoints; Survival analysis
Using multiple historical trials with surrogate and true endpoints, we consider various models to predict the effect of treatment on a true endpoint in a target trial in which only a surrogate endpoint is observed. This predicted result is computed using (1) a prediction model (mixture, linear, or principal stratification) estimated from historical trials and the surrogate endpoint of the target trial and (2) a random extrapolation error estimated from successively leaving out each trial among the historical trials. The method applies to either binary outcomes or survival to a particular time that is computed from censored survival data. We compute a 95% confidence interval for the predicted result and validate its coverage using simulation. To summarize the additional uncertainty from using a predicted instead of true result for the estimated treatment effect, we compute its multiplier of standard error. Software is available for download.
Randomized trials; Reproducibility; Principal stratification
Colon cancers with high-frequency microsatellite instability have clinical and pathological features that distinguish them from microsatellite-stable tumors. We investigated the usefulness of microsatellite-instability status as a predictor of the benefit of adjuvant chemotherapy with fluorouracil in stage II and stage III colon cancer.
Tumor specimens were collected from patients with colon cancer who were enrolled in randomized trials of fluorouracil-based adjuvant chemotherapy. Microsatellite instability was assessed with the use of mononucleotide and dinucleotide markers.
Of 570 tissue specimens, 95 (16.7 percent) exhibited high-frequency microsatellite instability. Among 287 patients who did not receive adjuvant therapy, those with tumors displaying high-frequency microsatellite instability had a better five-year rate of overall survival than patients with tumors exhibiting microsatellite stability or low-frequency instability (hazard ratio for death, 0.31 [95 percent confidence interval, 0.14 to 0.72]; P=0.004). Among patients who received adjuvant chemotherapy, high-frequency microsatellite instability was not correlated with increased overall survival (hazard ratio for death, 1.07 [95 percent confidence interval, 0.62 to 1.86]; P=0.80). The benefit of treatment differed significantly according to the microsatellite-instability status (P=0.01). Adjuvant chemotherapy improved overall survival among patients with microsatellite-stable tumors or tumors exhibiting low-frequency microsatellite instability, according to a multivariate analysis adjusted for stage and grade (hazard ratio for death, 0.72 [95 percent confidence interval, 0.53 to 0.99]; P=0.04). By contrast, there was no benefit of adjuvant chemotherapy in the group with high-frequency microsatellite instability.
Fluorouracil-based adjuvant chemotherapy benefited patients with stage II or stage III colon cancer with microsatellite-stable tumors or tumors exhibiting low-frequency microsatellite instability but not those with tumors exhibiting high-frequency microsatellite instability.
The addition of oxaliplatin to adjuvant 5-fluorouracil (5-FU) improves survival of patients with stage III colon cancer in randomized clinical trials (RCTs). However, RCT participants are younger, healthier, and less racially diverse than the general cancer population. Thus, the benefit of oxaliplatin outside RCTs is uncertain.
Subjects and Methods
Patients younger than 75 years with stage III colon cancer who received chemotherapy within 120 days of surgical resection were identified from five observational data sources—the Surveillance, Epidemiology, and End Results registry linked to Medicare claims (SEER–Medicare), the New York State Cancer Registry (NYSCR) linked to Medicaid and Medicare claims, the National Comprehensive Cancer Network (NCCN) Outcomes Database, and the Cancer Care Outcomes Research & Surveillance Consortium (CanCORS). Overall survival (OS) was compared among patients treated with oxaliplatin vs non–oxaliplatin-containing adjuvant chemotherapy. Overall survival for 4060 patients diagnosed during 2004–2009 was compared with pooled data from five RCTs (the Adjuvant Colon Cancer ENdpoinTs [ACCENT] group, n = 8292). Datasets were juxtaposed but not combined using Kaplan–Meier curves. Covariate and propensity score adjusted proportional hazards models were used to calculate adjusted survival hazard ratios (HR). Stratified analyses examined effect modifiers. All statistical tests were two-sided.
The survival advantage associated with the addition of oxaliplatin to adjuvant 5-FU was evident across diverse practice settings (3-year OS: RCTs, 86% [n = 1273]; SEER–Medicare, 80% [n = 1152]; CanCORS, 88% [n = 129]; NYSCR–Medicaid, 82% [n = 54]; NYSCR–Medicare, 79% [n = 180]; and NCCN, 86% [n = 438]). A statistically significant improvement in 3-year overall survival was seen in the largest cohort, SEER–Medicare, and in the NYSCR–Medicare cohort (non–oxaliplatin-containing vs oxaliplatin-containing adjuvant therapy, adjusted HR of death: pooled RCTs: HR = 0.80, 95% CI = 0.70 to 0.92, P = .002; SEER–Medicare: HR = 0.70, 95% CI = 0.60 to 0.82, P < .001; NYSCR–Medicare patients aged ≥65 years: HR = 0.58, 95% CI = 0.38 to 0.90, P = .02). The association between oxaliplatin treatment and better survival was maintained in older and minority group patients, as well as those with higher comorbidity.
The addition of oxaliplatin to 5-FU appears to be associated with better survival among patients receiving adjuvant colon cancer treatment in the community.
It is widely accepted that traditional models of clinical investigation are becoming unsustainable in oncology and that trials must become more efficient in matching effective treatments to the patients most likely to benefit. In 2008, gastrointestinal oncologists from many countries began a collaboration to improve the design and conduct of clinical trials in their field, through the auspices of a French/U.S. charitable foundation, ARCAD. Whether this model of academic collaboration will be judged a success will depend on the quality of its scientific output during the next few years and whether this output, alongside that of other scientists, groups, and institutions, ultimately leads to more efficient trials and improved treatment options for patients.
Gastrointestinal neoplasms; Clinical trials; Drugs; Investigational; Database; Data interpretation; Statistical
Symptoms and complications of metastatic colorectal cancer (mCRC) differ by metastatic sites. There is a paucity of prospective survival data for patients with peritoneal carcinomatosis colorectal cancer (pcCRC). We characterized outcomes of patients with pcCRC enrolled onto two prospective randomized trials of chemotherapy and contrasted that with other manifestations of mCRC (non-pcCRC).
A total of 2,095 patients enrolled onto two prospective randomized trials were evaluated for overall survival (OS) and progression-free survival (PFS). A Cox proportional hazard model was used to assess the adjusted associations.
The characteristics of the pcCRC group (n = 364) were similar to those of the non-pcCRC patients in median age (63 v 61 years, P = .23), sex (57% males v 61%, P = .23), and performance status (Eastern Cooperative Oncology Group performance status 0 or 1 94% v 96%, P = .06), but differed in frequency of liver (63% v 82%, P < .001) and lung metastases (27% v 34%, P = .01). Median OS (12.7 v 17.6 months, hazard ratio [HR] = 1.3; 95% CI, 1.2 to 1.5; P < .001) and PFS (5.8 v 7.2 months, HR = 1.2; 95% CI, 1.1 to 1.3; P = .001) were shorter for pcCRC versus non-pcCRC. The unfavorable prognostic influence of pcCRC remained after adjusting for age, PS, liver metastases, and other factors (OS: HR = 1.3, P < .001; PFS: HR = 1.1, P = .02). Infusional fluorouracil, leucovorin, and oxaliplatin was superior to irinotecan, leucovorin, and fluorouracil as a first-line treatment among pcCRC (HR for OS = 0.62, P = .005) and non-pcCRC patients (HR = 0.66, P < .001).
pcCRC is associated with a significantly shorter OS and PFS as compared with other manifestations of mCRC. Future trials for mCRC should consider stratifying on the basis of pcCRC status.
Among patients with resected colon cancer, black patients have worse survival than whites. We investigated whether disparities in survival and related endpoints would persist when patients were treated with identical therapies in controlled clinical trials.
We assessed 14 611 patients (1218 black and 13 393 white) who received standardized adjuvant treatment in 12 randomized controlled clinical trials conducted in North America for resected stage II and stage III colon cancer between 1977 and 2002. Individual patient data on covariates and outcomes were extracted from the Adjuvant Colon Cancer ENdpoinTs (ACCENT) database. The endpoints examined in this meta-analysis were overall survival (time to death), recurrence-free survival (time to recurrence or death), and recurrence-free interval (time to recurrence). Cox models were stratified by study and controlled for sex, stage, age, and treatment to determine the effect of race. Kaplan–Meier estimates were adjusted for similar covariates to control for confounding. All statistical tests were two-sided.
Black patients were younger than whites (median age, 58 vs 61 years, respectively; P < .001) and more likely to be female (55% vs 45%, respectively; P < .001). Overall survival was worse in black patients than whites (hazard ratio [HR] of death = 1.22, 95% confidence interval [CI] = 1.11 to 1.34, P < .001). Five-year overall survival rates for blacks and whites were 68.2% and 72.8%, respectively. When subsets defined by sex, stage, and age were analyzed, overall survival was consistently worse in black patients. Recurrence-free survival was worse in black patients than whites (HR of recurrence or death = 1.14, 95% CI = 1.04 to 1.24, P = .0045). Three-year recurrence-free survival rates in blacks and whites were 68.4% and 72.1%, respectively. In contrast, recurrence-free interval was similar in black and white patients (HR of recurrence = 1.08, 95% CI = 0.97 to 1.19, P = .15). Three-year recurrence-free interval rates in blacks and whites were 71.3% and 74.2%, respectively.
Black patients with resected stage II and stage III colon cancer who were treated with the same therapy as white patients experienced worse overall and recurrence-free survival, but similar recurrence-free interval, compared with white patients. The differences in survival may be mostly because of factors unrelated to the patients’ adjuvant colon cancer treatment.
The categorical definition of response assessed via the Response Evaluation Criteria in Solid Tumors has documented limitations. We sought to identify alternative metrics for tumor response that improve prediction of overall survival.
Individual patient data from three North Central Cancer Treatment Group trials (N0026, n=117; N9741, n=1109; N9841, n=332) were used. Continuous metrics of tumor size based on longitudinal tumor measurements were considered in addition to a trichotomized response (TriTR: Response vs. Stable vs. Progression). Cox proportional hazards models, adjusted for treatment arm and baseline tumor burden, were used to assess the impact of the metrics on subsequent overall survival, using a landmark analysis approach at 12-, 16- and 24-weeks post baseline. Model discrimination was evaluated using the concordance (c) index.
The overall best response rates for the three trials were 26%, 45%, and 25% respectively. While nearly all metrics were statistically significantly associated with overall survival at the different landmark time points, the c-indices for the traditional response metrics ranged from 0.59-0.65; for the continuous metrics from 0.60-0.66 and for the TriTR metrics from 0.64-0.69. The c-indices for TriTR at 12-weeks were comparable to those at 16- and 24-weeks.
Continuous tumor-measurement-based metrics provided no predictive improvement over traditional response based metrics or TriTR; TriTR had better predictive ability than best TriTR or confirmed response. If confirmed, TriTR represents a promising endpoint for future Phase II trials.
continuous; tumor measurement; RECIST; prediction; survival
Intermediate outcome variables can often be used as auxiliary variables for the true outcome of interest in randomized clinical trials. For many cancers, time to recurrence is an informative marker in predicting a patient’s overall survival outcome, and could provide auxiliary information for the analysis of survival times.
To investigate whether models linking recurrence and death combined with a multiple imputation procedure for censored observations can result in efficiency gains in the estimation of treatment effects, and be used to shorten trial lengths.
Recurrence and death times are modeled using data from 12 trials in colorectal cancer. Multiple imputation is used as a strategy for handling missing values arising from censoring. The imputation procedure uses a cure model for time to recurrence and a time-dependent Weibull proportional hazards model for time to death. Recurrence times are imputed, and then death times are imputed conditionally on recurrence times. To illustrate these methods, trials are artificially censored 2-years after the last accrual, the imputation procedure is implemented, and a log-rank test and Cox model are used to analyze and compare these new data with the original data.
The results show modest, but consistent gains in efficiency in the analysis by using the auxiliary information in recurrence times. Comparison of analyses show the treatment effect estimates and log rank test results from the 2-year censored imputed data to be in between the estimates from the original data and the artificially censored data, indicating that the procedure was able to recover some of the lost information due to censoring.
The models used are all fully parametric, requiring distributional assumptions of the data.
The proposed models may be useful to improve the efficiency in estimation of treatment effects in cancer trials and shortening trial length.
Auxiliary Variables; Colon Cancer; Cure Models; Multiple Imputation; Surrogate Endpoints
The developmental pathway from discovery to clinical practice for biomarkers and biomarker-directed therapies is complex. While several issues need careful consideration, two critical issues that surround the validation of biomarkers are the choice of clinical trial design (which is based on the strength of the preliminary evidence and marker prevalence) and the biomarker assay related issues surrounding the marker assessment methods such as the reliability and reproducibility of the assay. This review focuses on trial designs for marker validation, both in the setting of early phase trials for initial validation, as well as in the context of larger definitive trials. Designs for biomarker validation are broadly classified as retrospective (i.e., using data from previously well-conducted, randomized, controlled trials) or prospective (enrichment, allcomers or adaptive). We believe that the systematic evaluation and implementation of these design strategies are essential to accelerate the clinical validation of biomarker-guided therapy, thereby taking us a step closer to the goal of personalized medicine.
adaptive design; allcomers design; biomarker; enrichment design; hybrid design; randomized controlled trial
Although systemic chemotherapy in patients with unresectable metastatic colorectal cancer (mCRC) is palliative in nature, some patients experience long-term remission beyond 5 years consequent to treatment with chemotherapy alone.
Patients and Methods
We reviewed clinical data from 32 prospective North Central Cancer Treatment Group chemotherapy trials in mCRC that enrolled patients from 1972 to 1995. Metastatic CRC was verified histologically. Excluded from analyses were patients who withdrew consent to the study, enrolled in > 1 study, were ineligible, or had major protocol violations. We defined patients with survival beyond 5 years from the initiation of systemic treatment of mCRC as long-term survivors (LTS).
A total of 36 of 3407 (1.1%) patients were LTS. A total of 13 patients (0.4%) are without evidence of disease or disease progression > 5 years from cessation of last chemotherapy, with a median follow-up of 10.6 years (minimum, 7.6 years). Long-term survivors were more likely to have received 5-fluorouracil (5-FU)–based treatment (33 of 2503 [1.3%]) as opposed to other, less effective therapy (3 of 904 [0.3%]), suggesting that the chemotherapy played an important role among LTS (P = .01). Clinical characteristics of LTS were similar to the overall population in terms of age, sex, performance status, and tumor grade.
This study establishes a baseline for long-term outcomes of mCRC in the era when effective treatment was limited to 5-FU. With the development of improved systemic therapy for mCRC, cure without salvage surgery might be possible for a small, but important number of patients. Clinical trials should follow patients for > 5 years to document the long-term outcomes.
5-Fluorouracil; Disease site; Leucovorin; Liver metastasis
Numeracy (www.mayoclinic.com/calcs) and Adjuvant! (www.adjuvantonline.com) are two web-based calculators widely used to estimate the prognosis and potential benefit of adjuvant 5FU-based therapy for patients with Stage II and III colon cancer. This study compares the predicted survival estimates from these models with the actual observed estimates in independent datasets derived from a population cohort and from clinical trials
The population cohort was derived from the British Columbia Colorectal Cancer Outcomes Unit database which identified referred patients with stage II and III colon cancer from 1995–1996 and 1999–2003. Patients enrolled in NCCTG trials 94651 and 914653 were included in the trials dataset. Patient and disease data were used to determine the predictions for 5-year relapse free and overall survival for both tools.
In the population-based dataset (N= 2033), Adjuvant! offered more reliable predictions of prognosis for patients treated with surgery alone, but similar reliability as Numeracy for patients treated with adjuvant 5FU. Both models tended to overestimate survival in 5FU treated patients with stage II disease. In the trials dataset of patients treated with surgery and 5FU (N= 1729), Numeracy and Adjuvant! demonstrated similar performance and improve correctness.
This independent validation analysis demonstrates that both Numeracy and Adjuvant! have similar predictive performance and acceptable reliability for patients with stage III disease. Survival outcomes of patients with stage II colon cancer treated with adjuvant 5-FU were slightly lower then estimated by either model.